mikebridge commented on PR #42052:
URL: https://github.com/apache/superset/pull/42052#issuecomment-4974392621
### How this change fits into query construction
`QueryContextFactory` is the backend normalization step between the
chart-data request and dataset SQL generation:
```text
Browser chart configuration
→ QueryObjectFactory
→ QueryContextFactory
→ dataset SQL generator
→ database
```
`QueryObjectFactory` parses a dashboard `time_range` into `from_dttm` and
`to_dttm`. Those values describe the bounds, but they do not identify the
physical datetime column that belongs in the SQL `WHERE` clause.
In this code path, `QueryObject.granularity` is the physical datetime column
used as the time-filter subject; the time grain such as hour/day/month is
represented separately. Given:
```python
granularity = "event_time"
from_dttm = ...
to_dttm = ...
```
the dataset SQL generator can produce:
```sql
WHERE event_time >= ...
AND event_time < ...
```
Before this change, `_apply_granularity()` only reconciled the x-axis and
temporal filters when `query_object.granularity` was already populated. For an
adhoc SQL-expression x-axis, the request could contain valid
`from_dttm`/`to_dttm` values but no granularity. The SQL generator therefore
had bounds without a physical column and omitted the time predicate, allowing
ClickHouse to read the full table and hit `max_rows_to_read`.
This patch adds a narrow fallback. When:
- the x-axis is an adhoc SQL expression;
- the query has no explicit granularity;
- at least one time bound exists; and
- the dataset main datetime column is present and temporal;
we set the validated main datetime column as the filter subject.
The immediate `return` is intentional. The rest of `_apply_granularity()`
handles explicitly selected granularities and may rewrite the temporal x-axis
or remove a temporal filter that it considers replaced. An inferred granularity
has a narrower purpose: supply the physical column needed for the time
predicate while leaving the SQL-expression grouping axis and independent
temporal filters unchanged.
The resulting query keeps the expression in `SELECT`/`GROUP BY` and adds the
dashboard bounds against the physical datetime column in `WHERE`.
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